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Computational Methods to Identify New Antibacterial Targets
Author(s) -
McPhillie Martin J.,
Cain Ricky M.,
Narramore Sarah,
Fishwick Colin W. G.,
Simmons Katie J.
Publication year - 2015
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.12385
Subject(s) - in silico , drug discovery , computational biology , computer science , complement (music) , docking (animal) , data science , antibacterial activity , bioinformatics , biology , medicine , bacteria , genetics , nursing , complementation , gene , phenotype
The development of resistance to all current antibiotics in the clinic means there is an urgent unmet need for novel antibacterial agents with new modes of action. One of the best ways of finding these is to identify new essential bacterial enzymes to target. The advent of a number of in silico tools has aided classical methods of discovering new antibacterial targets, and these programs are the subject of this review. Many of these tools apply a cheminformatic approach, utilizing the structural information of either ligand or protein, chemogenomic databases, and docking algorithms to identify putative antibacterial targets. Considering the wealth of potential drug targets identified from genomic research, these approaches are perfectly placed to mine this rich resource and complement drug discovery programs.